Ye Chuyang, Bogovic John A, Ying Sarah H, Prince Jerry L
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.
Departments of Radiology, Neurology, and Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Proc IEEE Int Symp Biomed Imaging. 2013 Dec 31;2013:49-52. doi: 10.1109/ISBI.2013.6556409.
The superior cerebellar peduncles (SCPs) are white matter tracts that serve as the major efferent pathways from the cerebellum to the thalamus. With diffusion tensor images (DTI), tractography algorithms or volumetric segmentation methods have been able to reconstruct part of the SCPs. However, when the fibers cross, the primary eigenvector (PEV) no longer represents the primary diffusion direction. Therefore, at the crossing of the left and right SCP, known as the decussation of the SCPs (dSCP), fiber tracts propagate incorrectly. To our knowledge, previous methods have not been able to segment the SCPs correctly. In this work, we explore the diffusion properties and seek to volumetrically segment the complete SCPs. The non-crossing SCPs and dSCP are modeled as different objects. A multi-object geometric deformable model is employed to define the boundaries of each piece of the SCPs, with the forces derived from diffusion properties as well as the PEV. We tested our method on a software phantom and real subjects. Results indicate that our method is able to the resolve the crossing and segment the complete SCPs with repeatability.
上小脑脚（SCPs）是白质束，是小脑通向丘脑的主要传出通路。利用扩散张量图像（DTI），纤维束成像算法或体积分割方法已能够重建部分SCPs。然而，当纤维交叉时，主特征向量（PEV）不再代表主要扩散方向。因此，在左右SCP交叉处，即所谓的SCP交叉（dSCP）处，纤维束会错误传播。据我们所知，以前的方法无法正确分割SCPs。在这项工作中，我们探索扩散特性，并试图对完整的SCPs进行体积分割。不交叉的SCPs和dSCP被建模为不同的对象。采用多对象几何可变形模型来定义SCPs每一部分的边界，其力源自扩散特性以及PEV。我们在软件模型和真实受试者上测试了我们的方法。结果表明，我们的方法能够解决交叉问题，并以可重复性分割完整的SCPs。
